Variability of groundwater fluoride and its proportionate risk quantification via Monte Carlo simulation in rural and urban areas of Agra district, India

Application of Monte Carlo simulation and artificial neural network model to probabilistic health risk assessment in fluoride-endemic areas

Groundwater contamination with fluoride is a considerable public health concern that affects millions of people worldwide. The rapid growth of urbanization has led to increase in groundwater contamination. The health risk assessment focuses on both acute and chronic health consequences as it investigates the extent and effects of fluoride exposure through contaminated groundwater. Fluoride exposure, especially in endemic locations, has serious health consequences, including dental and skeletal fluorosis. An accurate assessment of these hazards is essential for public health planning and mitigation actions. The present study uses Monte Carlo Simulation (MCS) and an Artificial Neural Network (ANN) model to perform a Probabilistic Health Risk Assessment on populations in fluoride-endemic areas. Analysis of the results of the study reveals that the concentration of fluoride ranged from 0.58 to 3.80 mg/L with an average of 2.30 mg/L across the Kasganj district, which was higher than permissible limits given by BIS and WHO. The highest value of hazard quotient of 3.29 for Children is found to be in the Durga Colony area, while the lowest value of the hazard quotient of 0.31 for adults is found to be in the Nadrai Gate area. The assessment of health risks revealed a high probability of non-carcinogenic disease from the consumption of groundwater containing fluoride. The ANN model has the R2 value of 0.9989 in training and 0.9870 in testing while RMSE value in training and testing was 0.02230 and 0.0267. The findings suggest that before being used, the groundwater in Kasganj, Uttar Pradesh, India, needs to be treated and made drinkable. The results emphasize the critical need for ongoing monitoring, public education initiatives, and implementing feasible mitigating techniques to lower fluoride exposure. The findings show that this hybrid model is excellent at addressing the numerous uncertainties associated with fluoride use, hence improving the reliability of health risk estimates in fluoride-endemic locations. The results offer vital information to help policymakers and local health officials create focused measures to safeguard public health in Kasganj.

Distribution characteristics and risk assessment of fluoride in surface water of urban typical rivers

Recent research on fluoride in water primarily focuses on groundwater; however, the potential environmental risks of fluoride in urban rivers should not be overlooked. In 2023, this study collected 135 surface water samples from the Ershibu River in Hefei, China, during various flood periods. Through descriptive statistical analysis, correlation analysis, principal component analysis-multiple linear regression (PCA-MLR) modeling, hazard quotient (HQ) assessment, and Monte Carlo simulation analysis, the spatial and temporal distribution, potential sources, and health risks of fluoride were investigated. The results showed that fluoride concentrations in the Ershibu River ranged from 0 to 1.38 mg/L. According to the PCA-MLR calculations, industrial pollution (73.92 %) was identified as the main source, followed by hydrogeochemical evolution (16.10 %) and agricultural activities (9.98 %). The HQ analysis revealed that the average exceedance rates of HQ for the five exposed populations were as follows: infants (64.45 %) > young children (2.22 %) = adults (2.22 %) > children (0) = teenagers (0). Therefore, relevant authorities should improve defluoridation facilities to reduce fluoride levels in industrial and agricultural wastewater and implement measures to protect public health. Future research should investigate the migration processes and toxicity mechanisms of fluoride more thoroughly.

Integrated study of hydrochemistry, quality and risk to human health of groundwater in the upper reaches of the Wulong River Basin

Groundwater, a vital source of water supply, is currently experiencing a pollution crisis that poses a significant risk to human health. To understand the hydrochemical formation mechanisms, quality and risk to human health of groundwater in the upper reaches of the Wulong River basin, 63 sets of groundwater samples were collected and analyzed. A combination of mathematical statistics, correlation analysis, Gibbs diagram, ion ratio, and cation exchange were comprehensively employed for hydrochemical analysis, and further water quality index (WQI) and human health risk assessment were conducted. The results indicate that groundwater is generally neutral to weakly alkaline. The dominant cations in the groundwater are Ca2+ and Mg2+, while the main anions are HCO3- and SO42-. The hydrochemical types of groundwater mainly include HCO3·SO4-Ca, HCO3-Ca and HCO3-Na. The diverse hydrochemical types are mainly due to the fractured and discontinuous nature of the aquifers. The hydrochemical characteristics are influenced by the dissolution of silicate and carbonate minerals, cation exchange processes, and anthropogenic pollution. The presence of NO3- in groundwater is primarily attributed to agricultural activities. The groundwater is mainly categorized as "Good" (36.6%) and "Poor" (60.8%). "Very poor" and "Excellent" categories are rare, accounting for only 1.2% and 1.4%, respectively, and no samples are classified as "Non-drinkable". The Ewi for NO3- is the highest, indicating severe contamination by anthropogenic NO3- pollution. Human health risk assessment reveals that water samples posing exposure risks account for 82.54% for children and 79.37% for adults. This study highlighted that anthropogenic nitrate pollution has deteriorated groundwater quality, posing risks to human health. It also suggests an urgent need to enhance research and protective measures for groundwater in similar regions, such as the Shandong Peninsula.

Geographical analysis of fluoride and nitrate and its probabilistic health risk assessment utilizing Monte Carlo simulation and GIS in potable water in rural areas of Mathura region, Uttar Pradesh, northern India

Human health is being increasingly exposed to fluoride and nitrate ingestion globally due to anthropogenic alternations in groundwater resources. In the present research work, a hazard quotient (HQ), Monte Carlo simulation (MCS), and geographic information systems (GIS) have been used to estimate the non-carcinogenic health risk of nitrate and fluoride in vulnerable adults, teenagers, and children living in far-flung areas of Uttar Pradesh, Northern India. About 110 samples from some nearby populations were collected and analyzed for nitrates by ion chromatography and fluoride by a fluoride-selective electrode. The results indicated that the concentrations of fluoride and nitrate in the sampling areas ranged from 0.21 to 1.71 mg/L and 0.4-183.54 mg/L, respectively, with mean concentrations of about 1.20 mg/L and 51.52 mg/L for fluoride and nitrate, respectively. The results indicated that 27.27 % of the fluoride samples (27 out of 110) and 45.45 % of the nitrate samples (44 out of 110) were above the standard limits set by WHO. The calculated average HQ values fluoride and Nitrate for children, teenagers and adults were 1.88, 0.98, 0.90 and 3.02, 1.57, 1.45 respectively The 95th percentile HQ values for fluoride were 2.87 for children and 1.03 for adults, while those for nitrate were 4.10 for children and 1.98 for adults. Results of the health risk assessment show that there is a high potential for both non-carcinogenic and cancer risks from fluoride and nitrate through the consumption of groundwater. The Monte Carlo simulation showed the uncertainties and increased risks for children; therefore, one can infer that rural groundwater of the Mathura region, Uttar Pradesh, India, must be treated to make it potable for consumption.

Hotspot mapping and risk prediction of fluoride in natural waters across the Tibetan Plateau

Intake of high fluoride concentrations through water affects up to 1 billion people worldwide, and the Tibetan Plateau (TP) is one of the most severely affected areas. Knowledge regarding the high fluoride risk areas, the driving factors, and at-risk populations on the TP remains fragmented. We collected 1581 natural water samples from the TP to model surface water and groundwater fluoride hazard maps using machine learning. The geomean concentrations of surface water and groundwater were 0.26 mg/L and 0.92 mg/L, respectively. Surface water fluoride hazard hotspots were concentrated in the north-central region; high fluoride risk areas of groundwater were mainly concentrated in the southern TP. Hazard maps showed a maximum estimate of 15% of the total population in the TP (approximately 1.47 million people) at risk, and 500,000 people considered the most reasonable estimate. Critical environment driving factors were identified, in which climate condition was taken for the vital one. Under the moderate climate change scenario (SSP2.45) for 2089-2099, the high fluoride risk change rate differed inside the TP (surface water -24%-55% and groundwater -56%-50%), and the overall risk increased in natural waters throughout the TP, particularly in the southeastern TP.